A hybrid ant colony algorithm for solving container loading

Jiamin Liu*, Xiaorui Zhang, Carsten Maple, Yong Yue

*Corresponding author for this work

Research output: Chapter in Book or Report/Conference proceedingConference Proceedingpeer-review

1 Citation (Scopus)

Abstract

Container loading is a combinatorial optimization problem in three-dimensional packing which is an area of cutting and packing. It belongs to a NP-hard problem. To solve this problem, a hybrid approach is proposed in this paper. The approach integrated a loading heuristic into an ant colony optimization algorithm. The loading sequence is generated by the ant colony algorithm which configures the quantity of pheromone trails, transition probability and objective function. The loading sequence is transformed into the loading layout of boxes by using a loading heuristic which combines the heuristic strategy of generated blocks and the method for handling remaining spaces. The approach is tested through the test instance. The experimental result has shown that the approach is superior to the DNA generic algorithm.

Original languageEnglish
Title of host publicationProceeding of 2012 International Conference on Information Management, Innovation Management and Industrial Engineering, ICIII 2012
PublisherIEEE Computer Society
Pages224-227
Number of pages4
ISBN (Print)9781467319324
DOIs
Publication statusPublished - 2012
Externally publishedYes
Event2012 International Conference on Information Management, Innovation Management and Industrial Engineering, ICIII 2012 - Sanya, China
Duration: 20 Oct 201221 Oct 2012

Publication series

NameProceeding of 2012 International Conference on Information Management, Innovation Management and Industrial Engineering, ICIII 2012
Volume3

Conference

Conference2012 International Conference on Information Management, Innovation Management and Industrial Engineering, ICIII 2012
Country/TerritoryChina
CitySanya
Period20/10/1221/10/12

Keywords

  • Ant colony optimization
  • Container loading
  • Heuristic
  • Remaining space
  • Utilization

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